Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer

Markus Brandt; Ulf Brefeld

Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer

Markus Brandt
, Ulf Brefeld

Technische Universität Darmstadt

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

6 Zitate (Scopus)

Abstract

We present a graph-based approach to analyzing player interaction
in team sports. A simple pass-based representation is presented
that is subsequently used together with the PageRank algorithm to identify the importance of the players. Aggregating player scores to team values allows for turning our approach into a predictor of the winning team. We report on empirical results on five German Bundesliga seasons.

Originalsprache	Englisch
Titel	Proceedings of the 2th Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2015
Redakteure/-innen	Jesse Davis, Jan Van Haaren
Seitenumfang	8
Erscheinungsort	Achen
Herausgeber (Verlag)	Sun Site Central Europe (RWTH Aachen University)
Erscheinungsdatum	2015
Seiten	10-17
Publikationsstatus	Erschienen - 2015
Extern publiziert	Ja
Veranstaltung	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML/PKDD 2015 - Porto, Deutschland Dauer: 07.09.2015 → 11.09.2015 http://www.ecmlpkdd2018.org/ http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=40580&copyownerid=30660

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Informatik
Wirtschaftsinformatik

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Brandt, M., & Brefeld, U. (2015). Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer. in J. Davis, & J. V. Haaren (Hrsg.), Proceedings of the 2th Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2015 (S. 10-17). (CEUR Workshop Proceedings; Band 1970). Sun Site Central Europe (RWTH Aachen University). https://dtai.cs.kuleuven.be/events/MLSA15/papers/mlsa15_submission_3.pdf

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Brandt, M & Brefeld, U 2015, Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer. in J Davis & JV Haaren (Hrsg.), Proceedings of the 2th Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2015. CEUR Workshop Proceedings, Bd. 1970, Sun Site Central Europe (RWTH Aachen University), Achen, S. 10-17, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML/PKDD 2015, Porto, Deutschland, 07.09.15. <https://dtai.cs.kuleuven.be/events/MLSA15/papers/mlsa15_submission_3.pdf>

Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer. / Brandt, Markus; Brefeld, Ulf.
Proceedings of the 2th Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2015. Hrsg. / Jesse Davis; Jan Van Haaren. Achen: Sun Site Central Europe (RWTH Aachen University), 2015. S. 10-17 (CEUR Workshop Proceedings; Band 1970).

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

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AB - We present a graph-based approach to analyzing player interaction in team sports. A simple pass-based representation is presented that is subsequently used together with the PageRank algorithm to identify the importance of the players. Aggregating player scores to team values allows for turning our approach into a predictor of the winning team. We report on empirical results on five German Bundesliga seasons.

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Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer

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